Traditional training may be accomplished using a live training aid limited by live geographical and performance based constraints. For example, a live training aid aircraft may be used to simulate a hostile threat and perform tactics associated with those of a hostile threat. A trainee may receive information concerning the scenario problem and assess the scenario and tactics thereof. The trainee then makes execution decisions based on the received information. For example, at a distance out of on-board sensor range, a live training aid simulating a hostile threat aircraft may not be a factor to friendly assets associated with the trainee aircraft. At this range, the trainee may only receive information concerning the live training aid via offboard sensors (e.g. datalink).
These live training aids, however, are constrained by physical boundaries making limited the training available to a trainee. For example, live training typically is performed with multiple platforms on a training range. A “range” as used herein may include a fixed, charted geographical section of airspace with 1) a horizontal boundary and 2) a lower vertical boundary and 3) an upper vertical boundary. For example, range airspace may have a an east west limit of 50 Nautical Miles (NM) and a north south limit of 60 NM while encompassing a trapezoidal shape normally associated with a radial/Distance Measuring Equipment (DME) from a Navigational Aid (navaid). This range airspace may exemplarily possess a lower vertical boundary or “floor” of 7000 ft. MSL and an upper vertical boundary “ceiling” of 50,000 ft. MSL.
For example, two aircraft filling a “Blue Air” role practicing friendly tactics while two aircraft filling a “Red Air” role are practicing hostile tactics would oppose each other within such a range. The Red forces presenting a problem against which the Blue Air forces may learn to solve through training. The Red forces are enlisted to provide scenario presentations as training aids for the Blue forces. These scenario presentations require separation between the forces for accuracy and consistency. Occasionally, atmospheric conditions (e.g., strong winds, cloud layers) preclude the Red forces from an accurate or valuable training scenario presentation.
Many high performance aircraft and operational capabilities of weapons systems may exceed the capabilities of a live training aid. For example, modern aircraft require large blocks of airspace both horizontally and vertically due to aircraft speed and altitude capabilities and ranges of ordinance and distances involved. Such large blocks of reserved space are difficult to arrange and finite in geography and suffer from additional limitations including stationary in location, impacted by weather, available at Air Traffic Control discretion, and shared with civilian aircraft. Live training aids may be constrained by service ceiling, maintenance issues and speed limitations limiting an accurate presentation of a high performance threat.
Virtual training aids may solve some of these limitations and provide a limited level of training. Virtual training aids may solve the issue of range but lack the capability for close in visual or local sensor based training. For example, the Blue forces may be presented a scenario in which the Red forces were beyond visual range (BVR) or beyond local sensor range. A BVR scenario may be virtually created and valuable training may occur during prosecution of the virtual training aids. The trainee may make valid operational decisions based on this BVR hostile threat aircraft data received.
However, once the virtual training aid reaches a point where the trainee sensors (radar, targeting pod, pilot's eyeballs) are realistically designed to image the training aid, negative training may result if the trainee's sensors do not successfully image the training aid. For example, at a specific range threshold, an aircraft radar is designed to successfully image a live target aircraft and display the imaged data to the trainee/pilot. Should the radar not image and display the target, the trainee may not receive the desired level of training. Similarly, at closer range, a trainee may expect to visually acquire the training aid and make further decisions based on the visual presentation. A virtual training aid is incapable of producing this actual visual image
Therefore, a need remains for training methods and systems which offer a virtual training aid unlimited by physical, geographic and behavior constraints of a live training aid while maintaining a realistic sensor-based problem for the trainee to solve to complete the scenario.